The present invention relates to an image data binary coding method for use in a printer, a scanner, a copier, a facsimile, etc. for reproducing multi-gradation image data in the form of a bi-gradation image.
An error diffusion method is well known for converting a multi-gradation image to a bi-gradation image.
FIG. 5 is a block diagram of a circuit for performing a conventional error diffusion method. Multi-gradation image data D0 of a target pixel to be converted to bi-gradation image data is read from image memory 100; a y-correction is performed, by reference to correction data stored in xcex3-correction ROM 101; the multi-gradation image data is transformed to multi-gradation image data pertinent to printing characteristics of an output device such as a printer. Multi-gradation image data D, after the xcex3-correction, is added with error correction E of the target pixel by adder 102 in error diffusion processing unit 107, and resultant output F is released as F=D+E.
Output F of the target pixel, added with error data E, is then compared with binary threshold Th by comparator 104. When F= greater than Th, comparator 104 releases a binary signal B of 1 (B=1). If F less than Th, a binary signal of 0 (B=0) is released. From the binary signal from comparator 104, subtracter 106 determines binary coding error Exe2x80x2 as Exe2x80x2=Fxe2x88x92Bxe2x80x2. When an input data has 256 levels of gradation (0 to 255), Bxe2x80x2 is given as Bxe2x80x2=255B. When D=230 and Th=128, binary output B is 1 (B=1) and binary coding error Exe2x80x2 is determined as
Exe2x80x2=Dxe2x88x92255B=230xe2x88x92255=xe2x88x9225 
For application to each pixel data thereafter, binary coding error Exe2x80x2 is weighted according to specific error matrix Mxy in weighting error calculator 105, and then, calculator 105 calculates error correction E and saves correction E in error memory 103. Adder 102 adds error correction E with succeeding multi-gradation pixel data, and the error diffuses.
In the above example, multi-gradation image data D of D=230 is compared with binary threshold Th of Th=128, and a resultant binary output is 1 at the level of 255 out of 256 levels. Then, a binary error of xe2x88x9225 is generated for multi-gradation image data D of 230. Weighting error calculator 105 weights and distributes the binary error to error memory 103 for adjacent pixels with the error matrix, and the error is reflected to the binary coding of the succeeding multi-gradation image data.
An example of error matrix Mxy used in the conventional error diffusion method is shown in FIG. 6. The pixel denoted by the symbol xe2x80x9c*xe2x80x9d is a target pixel to be subjected to the binary coding. An error generated during the binary coding of the target pixel is weighted according to the weighting factors of 7, 1, 5, and 3 shown in FIG. 6, and weighted errors are applied to the succeeding image data before the binary coding. For binary coding of the multi-gradation image data of the target pixel denoted by xe2x80x9c*xe2x80x9d, the weighted error is read out from error memory 103 and used for correcting the image data received from image memory 100.
The conventional error diffusion method permits a binary error generated during the binary coding of pixel data to be applied to the succeeding pixel data that is subjected to the binary coding, hence minimizing the error between the bi-gradation image data and the original multi-gradation image data.
The binary image generated by the error diffusion method has a smoother gradation and a higher resolution than a binary image generated by a common dithering matrix method. Hence, the error diffusion method is preferably applied to an ink jet printer or the like and regarded as an essential method for achieving a higher quality level of printing.
When a binary image generated by the error diffusion method is printed down with a common electronic photographic apparatus, dots of a printed pattern appear unstable hence causing a shape of a particle to be significantly deteriorated and making the quality of a printed image unfavorable.
This may be derived from the fact that the pattern of dots particularly in lower density regions is printed in an unstable manner by the electronic photographic apparatus and a dot gain is thus poor, while any ink jet printer can successfully print down discrete dots of a pattern. Also, in intermediate or high density regions, the dots of ink may be saturated too quickly, hence a declining reproducing of a gradation.
Moreover, printing with an electronic photographic apparatus possibly causes adjacent dots to overlap each other thus creating undesirably large dots. This may generate variations in the density throughout the regions at the same density, deteriorating the particles of dots.
Because of the above described aspects, the error diffusion method is not desirably applicable to the binary coding for an electronic photographic apparatus which produces a pattern of dots in an unstable manner in the reproduction. Yet, the error diffusion method is advantageous as higher in the smoothness of gradation and the resolution than the dithering methods. In a case that the error diffusion method is successfully used for binary coding with any electronic photographic apparatus, a resultant reproduced image will significantly be improved.
An image data binary coding method is provided for subjecting a pixel of a multi-gradation image to binary coding to generate a binary or bi-gradation image, which comprises acknowledging an arrangement of pixels around a target pixel through examining an on/off-state of each pixel of a binary form, calculating error correction data from the pixel arrangement, and carrying out the binary coding for multi-gradation image data.
As the error data for a binary form of the multi-gradation image data is corrected depending on a density of its actual printed form, unstable artifacts generated in the reproduction of printed dots can be suppressed during the binary coding. The bi-gradation image data processed by the error diffusion method can hence favorably be printed in dots.